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学生对 提供的 AI for Medical Diagnosis 的评价和反馈

1,344 个评分
294 条评论


AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. As an AI practitioner, you have the opportunity to join in this transformation of modern medicine. If you're already familiar with some of the math and coding behind AI algorithms, and are eager to develop your skills further to tackle challenges in the healthcare industry, then this specialization is for you. No prior medical expertise is required! This program will give you practical experience in applying cutting-edge machine learning techniques to concrete problems in modern medicine: - In Course 1, you will create convolutional neural network image classification and segmentation models to make diagnoses of lung and brain disorders. - In Course 2, you will build risk models and survival estimators for heart disease using statistical methods and a random forest predictor to determine patient prognosis. - In Course 3, you will build a treatment effect predictor, apply model interpretation techniques and use natural language processing to extract information from radiology reports. These courses go beyond the foundations of deep learning to give you insight into the nuances of applying AI to medical use cases. As a learner, you will be set up for success in this program if you are already comfortable with some of the math and coding behind AI algorithms. You don't need to be an AI expert, but a working knowledge of deep neural networks, particularly convolutional networks, and proficiency in Python programming at an intermediate level will be essential. If you are relatively new to machine learning or neural networks, we recommend that you first take the Deep Learning Specialization, offered by and taught by Andrew Ng. The demand for AI practitioners with the skills and knowledge to tackle the biggest issues in modern medicine is growing exponentially. Join us in this specialization and begin your journey toward building the future of healthcare....


Jul 2, 2020

It was a nice course. Though it covers basics. A follow-up advanced specilization can be made. Overall, it's sufficient for beginner for an engineer trying to learn application of AI for medical field

May 26, 2020

Throughout this course, I was able to understand the different medical and deep learning terminology used. Definitely a good course to understand the basic of image classification and segmentation!


251 - AI for Medical Diagnosis 的 275 个评论(共 293 个)

创建者 Kabakov B

Sep 8, 2020

It is so much better than courses from NLP specialization. But still too many "translate well-known formulae to python code" tasks.

创建者 Praneet S

May 23, 2020

last assignment of week 3 of this course is quite difficult to understand so I feel few more explanation should be mentioned

创建者 Taiki H

May 13, 2020

More detailed skills like data converion would be desirable, but still good starting point for beginners. Thanks!

创建者 Leon C

May 16, 2020

Very interesting theory. It could be more in-depth, and the notebooks with autograder contain some bugs.

创建者 Aldemar F V

Oct 16, 2020

Bueno el curso, los materiales. Por mejorar, que no hay buen seguimiento del avance de los estudiantes.

创建者 Faisal R

May 6, 2020

great course But not For the Pharmacy Student because You have to Know The Code Knowledge

创建者 Dishant S

Jul 21, 2020

The last coding exercise is quite lengthy and difficult, and the videos are too short

创建者 MD M R S

May 3, 2020

Liked this course. But some topics were not explained well. Like ROC curve

创建者 Alex K

Dec 22, 2020

Great course, I wished some content could have been covered more in depth

创建者 Jay

Jun 28, 2020

Best course for AI for medical diagnosis please do the pre-requisite.

创建者 Abbas A K

Jul 1, 2020

it was better to have more detail of loss functions for segmentation

创建者 Srinadh R B

Jul 5, 2020

As a case study for deep learning, this course helps us a lot.

创建者 Josh B

Dec 16, 2020

They started diving deeper towards the end of the course.

创建者 Zabirul i

Jul 25, 2020

Need to more clarify the notebook content in videos.

创建者 Sakshat R

May 5, 2020

Really nice and well-explained

创建者 Michel F

Jun 7, 2020

Last assignment was insane.

创建者 Pham N H

Jul 5, 2020

The problem is quite easy

创建者 Mimi C

Apr 25, 2020

The course is too basic.

创建者 Muntaha S

Nov 10, 2020

excellent course

创建者 Abdalkarem I F

Sep 10, 2020


创建者 Jakub V

May 11, 2020

This is interesting topic and I learnt how these things are done in medicine. However, from technical point of view, there are many issues. Bugs, typos, unexplained terms (dear learner, now please calculate background ratio) make this course messy and leaves the taste of "rushed product of corona crisis".

创建者 Volodymyr F

Apr 22, 2020

The course is very shallow. It explains in detail some simple concepts like Sensitivity and Specificity and then immediately touches complex topics like image recognition architectures, without much explanation. The course materials are unclear and the auto-grader is buggy.

创建者 Amina K

May 3, 2020

Instructions in the graded assignment did not have clear instructions. Sometimes, correct implementation was graded 'incorrect' by the grader. Also, videos of the ROC curve was not clear about why it is needed or what does it say about a model.

创建者 Tasneem. A

Apr 25, 2020

Hi Sir/Madam,

i took this course then realised it is beyond my understanding. I am a grade 12 student . please help me to cancel this ,so, i can take another course which can benefit me.

i will appreciate your help.

thanking you